How Biased are Your Features?: Computing Fairness Influence Functions with Global Sensitivity Analysis

1 June 2022

Papers citing "How Biased are Your Features?: Computing Fairness Influence Functions with Global Sensitivity Analysis"

5 / 5 papers shown

Title
FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Yining She Sumon Biswas Christian Kastner Eunsuk Kang 45 0 0 03 Jan 2025
How Spurious Features Are Memorized: Precise Analysis for Random and NTK Features Simone Bombari Marco Mondelli AAML 19 4 0 20 May 2023
Achieving Fairness at No Utility Cost via Data Reweighing with Influence Peizhao Li Hongfu Liu TDI 34 45 0 01 Feb 2022
Algorithmic Fairness Verification with Graphical Models Bishwamittra Ghosh D. Basu Kuldeep S. Meel FaML 16 18 0 20 Sep 2021
Towards A Rigorous Science of Interpretable Machine Learning Finale Doshi-Velez Been Kim XAI FaML 254 3,684 0 28 Feb 2017